Method and system for automatically creating an image advertisement

ABSTRACT

A system and method for generating an electronic document are provided. A request to generate an electronic document associated with a concept is received. Content for the electronic document is suggested based on the concept. A selection of the suggested content is received. An electronic document is automatically generated using the selected suggested content.

RELATED APPLICATIONS

This application claims priority to the U.S. patent application Ser. No.10/841,835 entitled “Method and System for Providing Targeted DocumentsBased on Concepts Identified Therein” filed May 10, 2004, which isincorporated herein by reference. This application is also related tothe U.S. patent application entitled “Method And System For Mining ImageSearches To Associate Images With Concepts” filed herewith Ser. No.10/880,375.

FIELD OF THE INVENTION

The present inventions relate to creating targeted graphicaladvertisements associated with one or more content-based concepts, suchas keywords and subject matters of interest.

BACKGROUND OF THE INVENTION

With the advent of the Internet, advertising over more interactive mediasuch as websites has become popular and inexpensive. The interactivenature of the Internet enables advertisements to be targeted to usersbased on highly specific user-requested content, and a successfuladvertisement can cost as little as a few pennies.

However, despite the initial promise of cheap and efficientwebsite-based advertisements, there remain several problems withexisting approaches. Advertisers are generally required to provide theirown advertisements to be displayed on websites. Creating a professionaladvertisement typically requires an advertiser to either maintain aninternal marketing department or outsource ad design to an advertisingfirm. Both options can be costly, particularly for small businesses.Designing graphical advertisements internally is often difficult forsmall business owners who have little bandwidth to master graphicalprocessing software, find or create attractive graphics that do notviolate another's copyright, and layout the ad in a professional-lookingformat. Even larger firms with dedicated marketing departments mustexpend considerable resources to maintain an effective and currentadvertising portfolio.

These and other drawbacks exist with current systems and methods.

SUMMARY OF THE INVENTION

Accordingly, various embodiments of the present inventions may bedirected to a system and a method for creating targeted graphicaladvertisements associated with one or more content-based concepts, suchas keywords and subject matters of interest.

In one exemplary embodiment, a system and method for generating anelectronic document are provided. A request to generate an electronicdocument associated with a concept is received. Content for theelectronic document is suggested based on the concept. A selection ofthe suggested content is received. An electronic document isautomatically generated using the selected suggested content.

In another exemplary embodiment, a computer-implemented method forgenerating a graphical advertisement is provided. An image and a requestto generate a graphical advertisement associated with the image isreceived. Graphics and text are suggested for the graphicaladvertisement based on the image. A keyword to associate with thegraphical advertisement is suggested. A selected keyword is received.The graphical advertisement is associated with the selected keyword. Aselection of the suggested graphics and text is received. A graphicaladvertisement is automatically generated using the selected suggestedgraphics and text.

In another exemplary embodiment, a computer-implemented method forgenerating a graphical advertisement is provided. Text and a request togenerate a graphical advertisement associated with the text is received.Graphics and words for the graphical advertisement are suggested basedon the text. A selection of at least one of the suggested graphics andwords is received. A keyword is suggested to associate with thegraphical advertisement. A selected keyword is received. The graphicaladvertisement is associated with the selected keyword. A graphicaladvertisement is automatically generated using the selected at least oneof the suggested graphics and words.

In another exemplary embodiment, a system for generating an electronicdocument is provided. An input device receives a request to generate anelectronic document associated with a concept and receiving a selectionof suggested content. A database stores content. A processorautomatically identifies and suggests content for the electronicdocument based on the concept. A document generator automaticallygenerates an electronic document using the selected suggested content.

In another exemplary embodiment, a computer-readable medium encoded withcomputer program code to generate an electronic document is provided.The program code is effective to perform the following: receive arequest to generate an electronic document associated with a concept;suggest content for the electronic document based on the concept;receive a selection of the suggested content; and automatically generatean electronic document using the selected suggested content.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a system for targeting an electronic document accordingto an embodiment of the invention.

FIG. 2 depicts a networked environment for operation of a system fortargeting an electronic document according to an embodiment of theinvention.

FIG. 3A is a flow chart illustrating an exemplary method for associatinga document with a concept according to an embodiment of the invention.

FIG. 3B is a flow chart illustrating an exemplary method for generatinga document based on a concept according to an embodiment of theinvention.

FIG. 4 depicts an exemplary document according to an embodiment of theinvention.

FIG. 5 depicts an exemplary image according to an embodiment of theinvention.

FIG. 6 depicts an exemplary document showing an ordered rankingaccording to an embodiment of the invention.

FIG. 7 shows an exemplary interface according to an embodiment of theinvention.

FIG. 8 shows an exemplary interface according to an embodiment of theinvention.

FIG. 9 shows an exemplary interface according to an embodiment of theinvention.

FIG. 10 shows an exemplary interface according to an embodiment of theinvention.

FIG. 11 shows an exemplary interface according to an embodiment of theinvention.

FIG. 12 shows an exemplary interface according to an embodiment of theinvention.

FIG. 13 shows an exemplary interface according to an embodiment of theinvention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENT(S)

Advertisements on websites are generally more effective when the adcontains graphics (e.g., images, animations, movies, etc.) and contenttargeted to its audience. More effective ads translate into moreselections of the ad and thus, more leads for the advertiser to turnthose prospects into customers. To target an advertisement to an enduser, concepts may be associated with the advertisement. For instance,an advertiser may associate one or more keywords with the ad so thatwhen a user requests a web page or other content associated with thesame or similar keywords, the ad may be provided with the requested webpage. This way, ads are provided to users who are more likely to beinterested in the ad.

An embodiment of the present invention provides for generatingelectronic documents such as graphical advertisements in response to arequest for an electronic document associated with a concept. Forinstance, some embodiments provide for receiving a request to create animage advertisement based on a supplied image or text, and then creatingan image advertisement based on the supplied image or text. Text andimages may be suggested for inclusion in the ad. Keywords may besuggested for association with the ad so that the ad may moreeffectively target the proper audience. The image advertisement may bestored for later provision to a targeted user. Accordingly, a documentsuch as a graphical advertisement may be generated quickly and cheaplywithout learning a software design program or paying an outside designfirm.

When a user later requests a document associated with a specificconcept, one or more documents (such as an image advertisement) may beselected that are associated with a content-based concept related to thespecific concept. The one or more documents may be provided to the userin a list according to the degree of association between the specificconcept and the content-based concepts associated with each document, aswell as other factors. The documents are effectively targeted to theuser based on the specific concept associated with the user's request.

These actions may be performed automatically, i.e., by anymachine-executable process and/or a process that does not require humanintervention or input. When the concepts trigger relevant content orsearch results, the documents may be displayed based on a rank. Forexample, the documents may be ranked based on relevancy, performanceparameter (e.g., click through rate (CTR), conversion rate, performanceinformation, other measure of performance, etc.), price parameter (e.g.,an amount an advertiser is willing to pay for each click, bid amount,price information, other measure of price, etc.), and/or other factors.Documents such as graphical advertisements may be targeted to searchresults and/or content pages (e.g., web pages, emails, print media,etc.) on a wide variety of sites and other display environments.

While the term “advertisement” and “ad” may be used as an illustrativeexample, it should be appreciated that the same system and method may beapplied to other forms of documents or electronic documents. As usedherein, the term “document” and “electronic document” may encompass oneor more advertisements, content pages (e.g., web pages), search results,emails, applications, IM messages, audio content or files, video contentor files, other files, other data or applications that may reside on oneor several (e.g., a network) of computer systems, or other definableconcepts or content. A “document” may also comprise a portion of adocument.

Overview and System Architecture

FIG. 1 depicts a system 100 for associating documents with concepts andfor providing an electronic document in a targeted manner based on thecontent of the electronic document and an indicated interest of therequest responsive to which the electronic document (e.g., anadvertisement) may be delivered targeting an electronic documentaccording to an embodiment of the invention. The system may comprise: aserver 2, one or more providers 8, one or more document sources 12, oneor more end users 10, and one or more databases 50 operatively connectedto server 2. As used herein, the term “concept” and “idea” may refer toa concept, image, word, document, sound, location, content, or otheridea, or any combination thereof.

System 100 may enable server 2 to process content associations ofelectronic documents. Document sources 12, providers 8, and end users 10may communicate with one or more servers 2 via electronic communication,including Internet communications. Document sources 12, providers 8, andend users 10 may include or have access to one or more servers 2 forproviding functionality associated with electronic documents.

Information that may be communicated between and among server 2,providers 8, document sources 12, end users 10, and document requestors16 may include one or more of the following: document information,document content information, content identification information,concept association information, document performance information,provider information, document similarity information, concept/keywordprice information, performance information, document-concept associationinformation, and other information. The document information may includeone or more of the following: the document itself, audio-visual content(e.g., pictures of faces, song lyrics, etc.), identification of audioand/or visual content, concepts associated with the document or portionsthereof, any language(s) used in the document, length information,information regarding the type(s) of files in the document (e.g., html,doc, zip, etc.), type of document (advertisement, educational document),summary information, pornographic content, other offensiveness content(e.g., use of potentially offensive words), the identity of the documentowner and/or the document creator, information about the document'sintended audience (such as geographic area, age range, gender, race,national origin, religion, other demographic information), and any otherinformation related to a document or to the server 2, providers 8, ordocument sources 12.

In particular, providers 8, document sources 12, end users 10, andserver 2 (collectively and individually, “associating entities”) maygenerate document-concept and/or document-document associationinformation for one or more documents and concepts. For instance, theassociating entities may select a particular document from among aplurality of provided documents based on the documents' relevance to anidentified concept, such as a search query. The fact that a specificdocument was selected from among a plurality of documents associatedwith a concept may be association data.

This information may be provided to and used by the server 2. Forinstance, the associating entities may receive a document, such as animage ad, from the server 2 (or provider 8) and then provide associationinformation about the document (and/or other documents referenced orlinked to in the document) to the server 2.

It should be appreciated that non-association data may also be a form ofassociation data. For instance, if a document is rarely (or never)selected from among a group of documents associated with a concept, thedocument may be un-associated with the concept.

Document sources 12 may provide documents to server 2, or server 2 may“pull” or retrieve documents from document sources 12. For instance, thedocument source 12 may provide an image or advertisement to server 2 sothat the server 2 may then provide the image or advertisement to one ormore content providers 8, and the providers 8 may provide the ad to oneor more end users 10 (or server 2 may provide the ad directly to the enduser 10). Document sources 12 may include any content creator or contentprovider 8, such as an advertisement listings provider or server 2.

Document requestors 16 may request documents from the server 2. Documentrequestors may comprise end users 10, providers 8, document sources 12,and other entities. Document requestors 16 may request the server 2 togenerate one or more documents such as image and/or text advertisements,web pages, emails, etc.

Providers 8 may provide documents to one or more end-users 10 a-10 n.Providers 8 may include a content provider, search engine or otherentity that makes available information, services, and/or products overan electronic network, such as the Internet. A provider 8 may includeone or more of the following, for example: an advertisement listingsprovider, an electronic document provider, a website host, a server 2,any other entity that provides electronic documents to users or otherentities, or any other provider of content. A provider 8 may be adocument provider 12.

Each of provider 8, document source 12, document requestor 16, end user10, image reader module 28, document comparison module 32, other module46, server 2, or other entity may comprise an associating entity. Anassociating entity may comprise an entity that associates a documentwith a concept (or otherwise communicates such an association). Anassociating entity may be one or more persons, groups, and/orprocessors. For instance, a user 10 may select a search result from asearch result page displayed based on a search query, and it mayaccordingly associate the selected search result document with thesearch query concept. Providers 8 who pass user concept-documentassociations to the server 2 may comprise an associating entity. Theproviders 8 may be partners of an entity associated with operatingserver 2. An end user 10 may be one or more persons, computers, computernetworks, or other entity on a network. An end user 10 may request andreceive content from a provider 8 and/or server 2. Additionalparticipants may be included based on various applications.

The server 2 may comprise any server 2, hub, central processor,provider, search engine, or other entity in a network. A database 50coupled to the server 2 may include one or more databases 50-64. Also,databases 50-64 may comprise portions of a single database 50. It shouldbe appreciated that the databases 50-64 may or may not be physicallydistinct. The server 2 and its modules 20-46 may store and accessinformation stored in the database(s) 50-64.

Features of the server 2 and other system elements and methods are alsodisclosed in U.S. patent application Ser. No. 10/742,791 entitled“Method And System For Providing Targeted Graphical Advertisements”filed Dec. 23, 2003, U.S. patent application Ser. No. 10/812,417 (nowU.S. Pat. No. 7,533,090) entitled “System and Method for RatingElectronic Documents” filed Mar. 30, 2004, U.S. patent application Ser.No. 10/841,827 entitled “Automated Graphical Advertisement SizeCompatibility and Link Insertion” filed May 10, 2004 , U.S. patentapplication Ser. No. 10/841,834 (now U.S. Pat. No. 7,801,738) entitled“System and Method for Rating Documents Comprising an Image” filed May10, 2004, U.S. patent application Ser. No. 10/841,835 (now U.S. Pat. No.7,697,791) entitled “Method and System for Providing Targeted DocumentsBased on Concepts Automatically Identified Therein” filed May 10, 2004,and U.S. patent application Ser. No. 10/841,833 (now U.S. Pat. No.7,639,898) entitled “Method And System For Approving Documents Based OnImage Similarity” filed May 10, 2004, and U.S. patent application Ser.No. 10/880,375 entitled “Method And System For Mining Image Searches ToAssociate Images With Concepts” filed Jun. 30, 2004. These applicationsare incorporated herein by reference in their entirety. The disclosuresof these applications should not be interpreted to limit any of thefeatures described herein.

A content database 52 may store documents and/or data related to thedocuments, such as portions, images, and text of documents. The contentdatabase 52 may also store patterns, rules, and programming usable bythe image reader module 28 to identify patterns and images in imagedocuments such as graphical advertisements.

The documents may be received from document sources 12 and/or providers8. Documents may also be generated by the server 2. The documents may ormay not be associated with one or more concepts.

An image data database 54 may store image data. The image data may bereceived from a document source 12, and the image reader module 28. Forinstance, the image reader module 28 may read image data and store it inthe image data database 54. The image data database 54 may store imagesthat are available for use by the general public, e.g., in image ads.

The image data database 54 may also store a wide variety of images anddata used by Optical Character Recognition (“OCR”) (e.g., OCR processorsand/or software) and other image processors to process and identify textand images. For instance, the image data database 54 may store programsand files that define and describe various images and image types. Theprograms may also identify patterns in the document that can be used tocompare the document to other documents (e.g., by comparing the patternsin one document to the patterns in another). The image data database 54may store generic (and specific) images for comparison. For instance,the image data database 54 may store a generic image of an apple. Thedocument comparison module 32 may process an image of a fruit andcompare it to the stored image of the apple to determine whether the twoimages are sufficiently similar and accordingly determine whether theimage can be classified as an image of an apple.

A concept database 56 may store concepts associated with documents. Forinstance, one or more concepts may be associated with a document bycontent association module 24, and image reader module 28. Theassociated concepts may be stored in this database 56. Documentselection module 36 may access concept database 56 when selectingdocuments to distribute to end users and providers. For instance, inorder to select a document associated with a specific concept, thedocument selection module 36 may access the concept database to matchthe specific concept with one or more concepts in the database. In thisway, a document can be selected that is related to the specific concept.

A concept association database 58 may store document-conceptassociations (i.e., “concept association information”) and otherinformation generated by the image data module 28, as well as any otherinformation that may be relevant to evaluating the strength of adocument-concept association. For instance, the concept associationdatabase 58 may store information relating to number of clicks on adocument, number of times a document has been provided, click throughrate, etc.

A link database 60 may store linked documents as well as the linksthemselves. The links may comprise links used in text ads and image ads.Linked content may be associated with a document and may result inadditional associations between documents and concepts. For instance, ifa document is associated with a concept, a document linked to theoriginal document may be associated with the same (or similar) concept.

A performance database 62 may store document performance information,such as click through rate (CTR), cost per click (CPC), revenueinformation, and other information. The performance database 62 maystore data associated with cost per click (or other price parameter),including bid amounts, for each graphic and/or advertiser. Performancedata may also comprise how often a document is selected from a pluralityof documents associated with a concept.

A document association database 64 may store document-documentassociation information. It should be noted that document-documentassociations are one form of document-concept associations (becausedocuments are concepts as defined herein), so the information in thisdatabase may also be stored in database 58. Document-documentassociation information may comprise any of the following: one or moredocuments associated with a particular document, one or more commonconcepts or associations of one or more documents, similarity ratingsbetween documents, groupings of similar or related documents (e.g.,advertisements for the same product or from the same document source 12,or images that are associated with a similar concept such as aparticular movie), and other information regarding an associationbetween and among one or more documents. The information may be receivedfrom the document comparison module 32 or another module. The database64 may also store concept association information andperformance-related information, such as the CTR of documents that aresimilar or related to each other as well as the concepts (e.g.,keywords) associated with them. For instance, the database 64 mayidentify several image ads that have substantially identical content butdifferent keywords and different CTRs. The concept suggestion module 40may access the document association database 64 (or the conceptassociation database 68) to determine suggested concepts for a document.

Other database(s) 66 may store other information related to thedocuments, links, linked documents, document associating entities, andother information.

The server 2 may comprise one or more modules to process documents andcontent, document ratings and other entity ratings, trust scores (e.g.,of document sources), and other data. The modules of server 2 may store,access and otherwise interact with various sources of data, includingexternal data, databases and other inputs. The modules of server 2 maycomprise processors, databases, and other processing devices.

Target module 20 enables a document source 12 such as an advertiser tospecify a target (intended) audience. For example, an advertiser mayspecify a preferred language, country or other demographic preference.The advertiser may want to reach potential customers through a contentpage, search results page and/or other type of page. Accordingly, theadvertiser may select target criteria via the target module 20.

A content association module 24 may associate keywords, subject matter,ideas, images, and other concepts and content with one or more documents(or one or more portions thereof) or one or more other keywords,concepts, images, etc. The content association module 24 may associatekeywords and other ideas with a document based on information receivedfrom the modules, databases, and entities described herein, or any otherentity. In particular, the content association module 24 may receiveinformation from an entity that associates a document with a concept.The module 24 may use this information to associate a concept with adocument.

For instance, an end user 10 may select a document, such as a searchresult, from a plurality of documents associated with a concept, such asa plurality of search results received in response to a search query.The selected search result document may be associated with the searchquery concept. For instance, a user 10 may search an image database of asearch engine for an image associated with search query “AbrahamLincoln”. The search engine (e.g., server 2) may select a plurality ofimages (e.g., public images usable by the general public) from an imagedatabase (or otherwise access such images) and deliver the images to theuser 10 in response to the query. The images may be selected because atitle of the image or other image information was determined to beassociated with the search query. The user 10 may then select aparticular image document from the plurality of provided images. Basedon the user's selection, the server 2 may associate the selected imagewith the concept “Abraham Lincoln”. The server 2 may determine thatbecause the user 10 selected one of a plurality of images associatedwith “Abraham Lincoln”, the image document may be related to the“Abraham Lincoln” concept.

In this way, non-text documents or portions thereof may be identified orotherwise associated with words and other concepts. The server 2 mayalso determine additional information about documents and concepts basedon document-concept associations. Based on language identificationtechnology well-known in the art and other resources, the server 2 mayidentify that the concept “Abraham Lincoln” is associated with (or isidentified with) a person named Abraham Lincoln. The server 2 may alsodetermine that “Abraham Lincoln” is a famous person, e.g., based on thefact that there are a large number of images with his name in the title.Using the method described above, the server 2 may identify that animage is a picture of Abraham Lincoln. In the same way, a search for“Abraham Lincoln beard hat” may help the server 2 identify an image thatcontains a picture of Abraham Lincoln with a beard and wearing a hat.

The content association module 24 may also aggregate associations. Forinstance, if a large number of people select the same image of AbrahamLincoln in response to an “Abraham Lincoln” image search, then “AbrahamLincoln” may be identified with the image.

The aggregating methods and functions may be similar to those known inthe art and/or described elsewhere in this application and the citedU.S. patent applications. For instance, a concept may not be identifiedwith an image in a database until the image is associated with theconcept a certain number of times or by a certain number of users.

A feedback mechanism (e.g., item 1D in FIG. 5) may also be used toidentify images. In this case, an evaluator may provide feedbackcomprising information identifying one or more images or other contentin the document. This information may be used by the content associationmodule 24 to associate a concept (e.g., identification information) withthe identified images or the document as a whole.

Images and other documents associated with a concept may be providedwhen a document associated with that concept (or a related concept) isrequested. For instance, if a document requestor 16 (e.g., a user 10 orprovider 8) requests an image advertisement associated with car wax, oneor more images of a car may be provided. The image of a car may beidentified by the associating systems and methods described herein.

Any kind of document or content may be associated with other documentsand content. For instance, any user selection (e.g., selected document)may be associated with the user or with information associated with theuser. For instance, if a user 10 is known to be a botany enthusiast (oris otherwise strongly associated with plants), then documents selectedby, stored by, viewed by, or otherwise associated with the user 10 maybe associated with botany. Images viewed by the user 10 may beidentified as being more likely to be images of flowers. Productspurchased by the user 10 may be (loosely) associated with the concept ofplants. Links selected on a web page may be determined to be more likelyto be related to botany than other links on the page.

In short, every choice made by a human (or processor) can be the basisfor associating (a) information associated with the chooser with (b)information associated with the choice, such as the chosen object orconcept. Such associations may be stored in the content associationmodule 24.

The association information may be used in selecting content to provideto users 10, providers 8, and other entities. In particular, theassociations can be used to determine the preferences (e.g., consumerpreferences) of a person. For instance, ads may be targeted to aspecific individual based on concepts associated with the individual orconcepts associated with features of the individual such as theindividual's neighborhood, age, or other information.

For instance, the concept association module 24 may determine that males(or another identifiable group) are more likely to select documents ofone type (sports-related documents) than another type (homedecoration-related documents). Accordingly, the concept of sports may beassociated with the male gender. When a male requests a document, theserver may assign a preference to sports-related in selecting andranking content for provision to the male user. Groups may be identifiedby any common feature, such as geography, identified preferences,occupation, hobbies, time zone, gender, age, nationality, language, etc.

The content association module 24 may receive information describing thetext and images of an image ad from the image reader module 28 or otherentity. This may occur after the image is processed by the image readermodule 28. Based on the information describing the text and images (orother content), the content association module may associate keywordswith the document. In the case of the image and text of the image ad ofFIG. 5, the content association module may associate the ad with thekeywords “8 mm film,” “16 mm film,” and “35 mm film,” and “filmequipment.” The content association module 24 may store the contentassociations in the concept database 56. When a document associated witha concept is subsequently requested, a document may be selected (e.g.,by the document selection module 36) that has keywords related to theconcept. For instance, if a document associated with “4 mm film” isrequested, the document of FIG. 5 may be provided because “4 mm film” isclosely related to the identified keywords associated with FIG. 5. Forinstance, the concept “4 mm film” and the keywords of FIG. 5 may beclosely related in semantic space.

In some embodiments, the content association module 24 may receivepreference information from document sources 12. For instance, onedocument source 12 a, such as an advertisement listings provider, mayrequest that a particular image ad provided by the source 12 a (e.g.,the ad shown in FIG. 5) be associated with the phrase “digital film”.The content association module 24 may accordingly associate the image adwith the phrase “digital film,” or any other requested keyword orsubject matter of interest.

In some embodiments, the content association module 24 may associatedocuments with concepts and/or subject matters of interest based oninformation received from the concept suggestion module 40. Forinstance, the concept suggestion module 40 may indicate that the adshown in FIG. 5 should be associated with the word “film”.

Image reader module 28 may comprise one or more computers or dataprocessors equipped with one or more optical sensors. The opticalsensors of the image reader module 28 may be equipped to identify and/orread optical data from the image of the document (e.g., from a pictureor photocopy of an image ad). It may perform these functionsautomatically. The image reader module 28 may also process a computerfile storing the document or image (e.g., a .pdf or .tif file) ratherthan optically reading a physical embodiment of the document. In someembodiments, an optical sensor may first “read” a physical embodiment ofthe document and convert optical image data into a file (e.g., a .pdffile, .tif file, or other image file format). In other words, the imagereader module 28 may “read” and process the image information of adocument in a manner analogous to how a human's eyes and brain read andprocess text and images from a page of a newspaper.

The optical sensor may use a laser, scanner, or other optical inputdevice to read and capture image data from a physical embodiment of thedocument (e.g., a paper copy of a text document, or a photograph of animage). Scanners that convert images into electronic files (e.g., .pdfor .tif files) are well known in the art. The image reader module 28 maythen process the file. For instance, the optical processor may use OCRto recognize or identify patterns in the stored optical data. Some typesof OCR involve the translation of optically scanned bitmaps of printedor written text characters into character codes, such as ASCII.

By processing optical data from the image of the document, variousoptical scanning technologies may enable the optical processor toidentify characters and images from the document. For instance, OCRtechnology (e.g., OCR scanners and software) may enable an image readermodule 28 to identify text characters in a document.

Instead of identifying merely text and other “characters”, the module 28may recognize and identify images. For instance, the module 30 may readan image and determine that the image contains a picture of a filmprojector, a bottle of beer, a person (in varying states of dress), oranother object.

The image reader module 28 may accordingly identify specific images(e.g., a famous person's face, a ham sandwich, a soft drink, a pizza, alocation such as a schoolyard, etc.) by identifying patterns in an imageor other document, such as geometric patterns. Geometric and otherpatterned rules for recognizing content may be stored in the image datadatabase 54.

The module 28 may also determine other optical data relating to theimage, such as image colors, color schemes, patterns, and otherinformation.

An advantage of using the module 28 to determine concept associationinformation is that concept association information can be determined(e.g., automatically, without human intervention). Because the server 2may receive and distribute thousands, millions, and/or billions ofdifferent documents, the transaction and administrative costs ofmanually reviewing each document may be prohibitive and/or expensive.

It should be further understood that the image reader module 28 may beconfigured to process and identify concepts based on sounds, animations,video, pop-up ability, and other audio-visual information in documents.Accordingly, the module 28 may further comprise speakers, microphones,and audio/video processors.

The image reader module 28 may accordingly be used to associate conceptswith a document as discussed above. These associations can be used whena document is requested from the server 2, e.g., by the documentrequestor 16, provider 8, or end user 10. For instance, if provider 8requests an image of an apple, the server may identify an imageassociated with the word “apple” based on the concepts associated withthe image and deliver the image to the provider 8.

Similarly, the image reader module 28 may be used to search for imagesof an apple (or images or other documents otherwise associated with aconcept). When an image associated with a concept is requested, theimage reader module 28 may process images in a database (e.g., contentdatabase 52 or image data database 54) to find one or more imagesassociated with the requested concept (e.g., “apple”). In other words,the concepts need not be pre-associated with the images.

The image reader module 28 may use different algorithms to search fordifferent types of content. For instance, one processing algorithm maybe used to search for images of persons, and another processingalgorithm may be used to search for images of real estate. Also,different algorithms may be used based on the type of media, e.g., afull motion video document may require different searching andprocessing algorithms than a still images document.

A document comparison module 32 may compare a document (e.g., an imageor portion thereof) to one or more other documents (e.g., images orportions thereof stored in the content database 52 and image datadatabase 54). Specifically, the document comparison module 32 maycompare an image from one document source 12 a to one or more documentsfrom the same document source 12 a already stored in the contentdatabase 52 or image data database 54. For instance, the documentcomparison module 32 may determine whether a document is identical to(or substantially identical to) another document. The documentcomparison module 32 may also determine a degree of similarity betweentwo or more documents (e.g., that a document is 80% similar to anotherdocument).

The document comparison module 32 may compare two or more documents bycomparing processed data associated with the images. For instance, themodule 32 may process image data files received from the image readermodule 28. The document comparison module 32 may compare the images,text, formatting, and patterns of one document to that of another. Forinstance, the module may identify that two different documents containthe same (or similar) image of an apple and the same (or similar) textdescribing an orchard.

The document comparison module 32 may determine a similarity ratingbetween two or more documents and associate similar documents with eachother. It should be noted that similarity ratings are a form ofassociation between documents.

Accordingly, the document comparison module 32 may identify concepts(e.g., text, images, sounds, etc.) in one document by identifying theconcepts of a substantially similar or identical document.

For example, one or more human associating entities may associate afirst document with several concepts, such as an apple, an orchard, anda peach. Also, the advertisement listings provider may bid on thekeywords “red apple” for the first document. This information may bestored in the content database 52, the concept database 56, and thedocument association database 54. The document comparison module 32 mayidentify that a second document is substantially identical to thisdocument, e.g., because the second document has nearly identical textand images (regardless of whether the document comparison module canidentify the actual content of the images). Because the two documentsare similar and the first document is associated with “red apple,”“orchard,” and “peach,” the second document may be associated with thesame concepts.

It should be understood that a document may be associated with conceptsother than words. For instance, a document can be associated withimages, sounds, and patterns. For instance, a vacation advertisement canbe associated with sound files of seagulls and waves crashing on aseashore, and pornographic advertisements can be associated withpatterns that indicate a high presence of human flesh (and nudity).

Although one document may be determined to have nearly identical textand images but different formatting, the document comparison module 32may determine the (relative) equivalence of the two documents. For(substantially) identical documents, the image reader module 28 mayindicate that the document is (substantially) identical to anotherdocument and identify the other document. If a first document isidentified to be substantially identical to a second document alreadystored in the database, it may receive the same concept associationinformation as the first document. Further, if a document contains animage (such as an apple) that is nearly identical to a stored image(another apple), the document comparison module 32 may determine thatthe document contains an image of an apple. The content associationmodule 24 may accordingly associate the document with the keyword“apple,” and/or the concept suggestion module 40 may accordingly suggestthat the document be associated with the concept “apple.”

It should be appreciated that two documents may be similar orsubstantially identical, or at least the content of the two documentsmay be similar or substantially identical, even if the documents havedifferent sizes, shapes, formats, colors, or other physical features.

A document selection module 36 may select and provide documents inresponse to a request for content from a provider 8, end user 10, orother entity. For instance, a children's book retailer may request anadvertisement to display on their site. In response, the documentselection module 36 may select a document based on informationassociated with the requestor or request (e.g., one or more conceptsassociated with the request).

The document selection module 36 may identify recipient information,e.g., by inspecting “cookies” on an end-user's computer. For instance,the document selection module 36 may identify preferences of an end user10 based on prior information received from the end user, such asconcept association information for a prior provided document.Information enabled or identified by the document selection module 36may be stored in the concept association database 58.

A rank module 38 may determine a rank of the ad, graphic, or otherdocument. The rank of the document may refer to the placement of thedocument, or the placement of one or more documents within one or moreother documents. For instance, a higher ranked document may be displayedin a position higher (e.g., closer to the top of a web page) thananother document. In FIG. 6, advertisement 1E may be considered to bedisplayed in a higher rank than advertisement 1F. The rank of a specificdocument may be based on performance and pricing information of thedocument, the document source, the relevance of the document to arequested concept, and other criteria.

The rank module 38 may determine the rank (ordering) of a plurality ofads. It also may determine the rank of search results or otherdocuments. For instance, a link to the web pages most closely related toa search query may be ranked higher than those that are not in a searchresults page. The rank of a document (or document link) may bedetermined by any information associated with the document. Inparticular, the rank of a document may be based on associationinformation determined by the content association module 24 and/orstored in the document association database 64. For instance, searchresult images may be ranked according to how strongly they areassociated with a particular concept, based on prior user associationsof the document with the concept (or related concepts). Thus, if aparticular image is usually selected by users who search for “BritneySpears,” then this image will likely be ranked very high when someonesearches for images of “Britney Spears.”

Generally, the higher (or more prominently) the document is displayed,the more likely an end-user will be to take notice, thereby improvingthe potential for a click through (e.g., an end-user clicking on thedocument). According to one example, the ranking of the document may bedetermined by multiplying the cost per click (CPC) and the click throughrate (CTR). Other methodologies for ranking documents may beimplemented. For example, other price parameters and/or performanceparameters may be considered.

Based on differences in customer behavior, the performance parameter forcontent pages and search pages may be different. Other adjustments maybe applied for different types of pages.

An auction process for determining which advertisement to show in whichplacement may become more complicated as the pricing for graphicaladvertisements may have a premium associated with the display. Forexample, placement of advertisements may be based on a click throughrate and cost per click (e.g., bid amount or any amount offered by anadvertiser) combination (e.g., CTR*CPC). In another example, advertisersmay be charged a higher rate for graphical advertisements based on ahigher likelihood that the advertisement would be selected. Further,additional costs may be associated for additional enhancements (e.g.,animation, sound, music, size, shape, etc.) or other features that mayincrease the advertisement's likelihood of being selected.

In addition, rank module 38 may also determine a position for thegraphical advertisement or other document. Some advertisements may bedisplayed as a banner, across the top of a page (e.g., search page,content page, etc.), along the side of search results, and anywhere elseon the page.

A concept suggestion module 40 may suggest concepts to associate with adocument. For instance, the concept suggestion module 40 may identifyconcepts or subject matters of interest that may be associated with(and/or included in) a particular document. The module 40 may pass thesesuggestions to a document source 12, content association module 24,document creation module 42, document requestor 16, and/or otherentities. The document requestor 16 (or other entity) may then selectone or more concepts and/or subject matters of interest based on thesuggested concepts.

To identify suggested concepts to associate with (e.g., include in orsuggest to be included in) a particular document such as an image ad,the concept suggestion module 40 may process document information (ordocument request information) from the document requestor 16, documentcreation module 42, concept database 56, link database 60, performancedatabase 62, document association database 64, and any other database 66or entity. For instance, the concept suggestion module 40 may suggestone or more keywords, images, subject matters of interest to associatewith a specific document based on any of the following factors: (1) thetext, images, links, and other content identified in the specificdocument; (2) the keywords and/or subject matters of interest selectedfor and/or associated with similar documents; (3) the performance of thesimilar documents (e.g., based on keyword and document similarity); (4)the performance of the specific document (e.g., the document's CTR usinga particular keyword); (5) the performance of related or similardocuments using a specific keyword (such as the CTR for a similardocument using a specific keyword); (6) the cost of a particular conceptof keyword; (7) and any other factors.

The concept suggestion module 40 may rate a variety of suggestedconcepts. For instance, the module 40 may suggest that the document ofFIG. 5 be associated with the word “film” and “8 mm,” but the module 40may also indicate that selecting the word “film” is most likely to leadto the highest CTR.

Document creation module 42 may create documents such as text and imageadvertisements. The documents may be created at the request of documentrequestor 16 or any other entity. Document creation module 42 mayreceive a request to create a document from document requestor 16.Requestors may specify concepts such as keywords, text, and images toassociate with one or more generated documents. Document creationrequests may also specify formatting and other criteria and preferences,such as the font, size, shape, color, and language of images, text, andother content that may be included in a document. Document creationrequests may also specify other preference information associated with adocument, such as a bid amount, conversion rate, keyword, or otherinformation. Document creation module 42 may use interfaces such asthose shown in FIGS. 7-13 during the document creation process. Themodule 42 may accept concepts, preferences, and other inputs from thedocument requestor 16.

Document format module 44 may format (or re-format) documents. Documentsmay be formatted according to display requirements or the preferences ofcontent requestors or providers. Document format module 44 may format(or re-format) the font, size, shape, color, and language of images,text, and other content that may be included in a document. Forinstance, a document of one resolution may be requested for display in adocument that requires a different resolution. Document format module 44may re-format the document so that it conforms to the appropriateresolution or other formatting constraint.

Other module(s) 46 may accomplish other functions related to targetingand/or rating electronic documents. Several additional server 2 andsystem 100 functions are described in the U.S. patent applications citedherein.

Illustrative System Network Environment

FIG. 2 depicts a networked environment for operation of a system fortargeting an electronic document according to an embodiment of theinvention. In such an environment, associating entities and providers 8may connect over a network 14, 15 to a server 2 (e.g., using a securehttps connection) to provide documents and concept associationinformation to server 2 and to receive documents and rating requestinformation from server 2. The server 2 may store the document, rating,and performance information in a database 50. The server 2 maydistribute the documents through various forums or feeds, includingdirect distribution in print media, providing the documents on one ormore web sites affiliated with the server 2 and through providers 8. Itshould be noted that providers may comprise syndication partners of theserver 2 (e.g., connected over network 14 or 15 depending on securitydesired), content systems (e.g., with associated content databases) andsearch engine systems operated by the server 2 or provider(s) 8.

Through these various forums, the documents provided to the providers 8may be included in pages (or other documents) displayed to end-users 10(often called an impression).

Each of server 2, associating entities, providers 8, and documentsources 12 may comprise computerized systems that include one or more ofthe following systems: a web server 2, a database server 2, proxy server2, network balancing mechanisms and systems, and various softwarecomponents that enable the system to operate on the Internet or othernetwork type system. Additionally, networks 14 and 15, although depictedas http networks, may comprise other networks such as private lines,intranets, or any other network. In an exemplary embodiment, theconnection between a document source 12 such as an advertisementprovider and server 2 (and other connections such as between a provider8 and server 2) may comprise secure network connections to insure thatdata is not subject to attack or corruption by any hacker or other thirdparty. In addition, whereas two associating entities and two documentproviders 12 are depicted, it should be appreciated that one or moreassociating entities and one or more document providers 12 may beprovided in the network. Similarly, although one database 50 isdepicted, it should be appreciated that multiple databases 39 may beprovided and that such databases 39 may be connected to the server 2 viaany type of network connection, including a distributed architecture forserver(s) 2.

Similarly, provider 8 a may comprise any number of such systemsconnected to the associating entity or server 2 via any type of network,including an http or https network. Content provider 8 may comprise asystem such as server 2 that provides functionality for enablingconnection over the Internet or other network protocols. End users 10may comprise any user (such as users connected to the Internet) and maycomprise computerized systems that enable that connection through any ofvarious types of networks, including through Internet service providers,cable companies, and any other method of accessing data on the Internet.Providers 8 may comprise any system that distributes content such asadvertising to end-users 10.

Illustrative Associating Process

FIG. 3A is a flow chart illustrating an exemplary method for associatinga document with a concept.

In block 300, a request for a document associated with an idea isreceived. For instance, an end user may request the document from aserver. The request may be a request for search results (e.g., images)associated with a search query on a web page. The search query idea maybe “Star Wars actors.”

In block 310, a plurality of documents associated with the idea arepassed. The documents may be passed from the server to the end user(e.g., via a provider). The plurality of documents may be a plurality ofimages or other documents associated with the search query.

Each search result may comprise an image and a link to a documentassociated with the image (e.g., an expanded view of the image on a webpage). For instance, the search results may comprise a plurality ofimages associated with Star Wars. These may include images and movieclips from the movie containing images of the actors, pictures of one ormore Star Wars actors in another movie, images from the sequel “EmpireStrikes Back,” or other images related to (or not related to) Star Warsactors.

The search engine may select these images because the images have “StarWars” and/or “actor” in the title. The search engine may also identifyterms associated with “Star Wars actors,” such as “Harrison Ford” (anactor in Star Wars), and select images with those terms in the title.Because some images may have improper titles, the search engine mayselect an image of a doorknob instead of a Star Wars-related imagebecause the image was improperly titled “Star Wars cast” or “CarrieFisher” (a Star Wars actress).

The selected images may be provided to the user. For instance, aplurality of compressed images may be provided on a search results page.Each compressed image may comprise a link to a full-page image of thecompressed image.

In block 320, a selection of one of the plurality of documents isreceived. For instance, the server may receive a selection from the enduser of one of the plurality of images. The end user may click on a linkassociated with the image, and the click may trigger a request for theserver to provide the user with the selected document (e.g., a web pagedocument associated with the link). In the example above, the user mayselect an image of Mark Hamill holding a light saber.

In block 330, the selected document is associated with a concept basedon the idea. For instance, the selected document may be associated withthe idea itself or a concept related to the idea. In the example above,the picture of Mark Hamill may be associated with “Star Wars,” which isrelated to the idea “Star Wars actor.”

The selected document may be processed to identify concepts associatedwith the document. For instance, an image processor may process an imagedocument to identify images and text in the image. If the Mark Hamillimage had the words “jedi knight” at the bottom, the image processormight identify these words using OCR technology. Then, based on the factthat the words “jedi knight” are in the image and a user selected theimage after querying “Star Wars actor,” the server might associate theimage with “Star Wars,” “jedi knight,” “Mark Hamill,” and “AlecGuinness” (another actor who played a jedi knight in Star Wars).

Regardless, the one or more associations are based in whole or in parton the selection in block 320. Alternately, un-selected documents may beun-associated with the concept.

In block 340, one or more other documents are associated with a conceptbased on the association. For instance, related documents may beassociated with a concept that is the same as or related to the conceptassociated with the selected document. For instance, an image documentthat is determined to have a substantially similar image to that of theselected document may also be associated with “Mark Hamill.”

The selected document may be processed to determine whether otherdocuments are similar. Documents with a similar title (or other feature)may be associated with the original search query or another conceptrelated to the selected document.

It should be appreciated that “associate” may comprise “identify.” Thecontent of an image may be identified (and thus “associated” with theidentified material) based on user associations rather than a first-handdetermination of the content of the image (or other document). If twomillion people who search for “Britney Spears” click on the same imagesearch result, it can be reasonably inferred by the server that theimage comprises a picture of Britney Spears.

Even first-hand determinations of the content of a document (e.g., animage) can be informed by user associations. While a person or imageprocessor may identify that an image contains Luke Skywalker and a lightsaber, it may not be able to associate this image comes from a scenewhere Luke trains under Obi Wan Kenobi in the Millenium Falcon. However,user associations can make these connections. For instance, if 9 out of10 users select this image from a plurality of search results related tothe search query “Luke Skywalker Ben Kenobi training Millenium Falcon,”a server may associate the image with each of these terms or intelligentcombinations thereof (e.g., it may associate the image with an interiorimage of the Millenium Falcon rather than an exterior image, and it mayrecognize that Luke rather than Ben is engaged in training).

It should be appreciated that the document associations may change asnew information and associations are received. For instance, a newassociation for one document may change the associations of a relateddocument.

In block 350, a second request for a document is received. This blockmay function in the same manner as block 300. Another user may request asearch result related to a second query. The second query may comprise“Star Wars jedi.”

In block 360, a document is passed based on the association and thesecond request. This block may function in a manner similar to thatdescribed for block 310. However, at least one document that is passedis based on the association.

In the above example, the Mark Hamill image may be provided along with aplurality of other search result images. The Mark Hamill image may beselected for inclusion based on its prior association with the words“Star Wars actor.” Without the prior association, the server may nothave recognized that the Mark Hamill image is related to Star Warswhatsoever.

Even if the Mark Hamill image may have been recognized as a relevantsearch result, the image may be displayed in a higher rank based on thestrength of its association with the keywords in the search. The priorassociation may have effectively strengthened the association betweenthe image and the term “Star Wars.” Thus, the image may appear 2^(nd)from the top instead of 7^(th) from the top of the web page searchresult.

Illustrative Document Generation Process

FIG. 3B is a flow chart illustrating an exemplary method for generatinga document based on a concept.

In block 301, a request to generate a document associated with an ideais provided. The request may be made by a document requestor (such as anadvertiser). The request may comprise a request for the server togenerate a text and/or image advertisement based on an idea/concept suchas the advertiser's slogan, product name, or other concept. The documentrequestor may access a server website to make the request. The servermay prompt the document requestor for information related to therequest, such as the idea associated with the request.

For instance, the server may request the name of the product,description of the product, product features, and the company motto. Thedocument requestor may provide those items, e.g., in a request field onthe web page. Some of the information that may be requested and/orprovided is shown and described with respect to FIGS. 7 and 8.

For example, an advertiser may submit an image of a car wax product anda description that says “car wax.” The advertiser may also indicate thatthe car wax “has superior durability and longevity and keeps your paintlooking new!” It should be noted that information provided by therequestor may collectively be considered a “concept” for purposes ofthis application.

A template of the document may be generated for purposes of creating thedocument in real-time as the requestor inputs additional information.

In block 311, concepts that may be associated with the document based onthe concept are suggested. For instance, the server may identifykeywords, images, text, and/or other concepts that may be associatedwith (and/or included in) the document to be generated. The images maybe selected based on the suggested concept. For instance, the server maysuggest a plurality of images of shiny sports cars to include in the adbased on the association between shiny sports cars and “car wax,”“paint,” and “new.” Suggested images may be presented in any format,such as that shown in FIG. 9. The server may suggest keywords such as“car wax,” “carwax,” and “car maintenance.” Suggested keywords may bepresented in any format, such as the format shown in FIG. 13. The servermay also suggest text and formatting for the ad, such as header in theupper left of the ad that states either “great deals on car wax” or“keep your car shiny and healthy.”

In block 321, performance and/or price information is passed, e.g., tothe document requestor. For instance, the prices of suggested keywordsmay be passed. Other information such as formatting options may bepassed to the requestor. This block 321 may occur at the same time asblock 311.

In block 331, preference, bid information, and/or selected concepts arereceived, e.g., from the document requestor. For instance, documentrequestor may select (and/or bid on) one or more keyword concepts toassociate with the ad. The document requestor may also select one ormore of the images suggested by the server. For instance, the documentrequestor may also select an image of a red Porsche for inclusion in thead. The document requestor may also select text to include in the adthat states “great deals on car wax.” The document requestor may alsoselect the keywords “car wax” and “carwax.”

The document requestor may also select the size, resolution, font, andother features of the image ad or other document. For instance, the carwax company may request a banner ad format and size, as well as a soundthat plays when the banner ad is displayed.

In block 341, the document is associated with selected concepts. Forinstance, the document may be associated with the selected keywords andthe associated bid prices.

In block 351, the document is generated based on the various inputs. Forinstance, the server may generate the document based on the selectedimages, format, and text. It should be appreciated that the document maybe generated over a period of time. For instance, the document may begenerated as a document requestor navigates through the various fieldsof a web page as shown in FIGS. 7-13. The resulting document may be animage ad, such as the image ad 1 shown in FIG. 5.

The document may also be stored.

In block 361, a request for a document associated with one or moreconcepts may be received. This action may occur in a mannersubstantially similar to that described for blocks 300 and 350. Forinstance, an end user may submit a search query on a search enginewebsite or request a website or other document. The search query maycomprise “car wax polish.”

In block 371, one or more documents may be selected based on theassociated concepts. For instance, the car wax advertisement may beselected for display based on an association between the advertisement'sselected keyword “car wax” and the search query “car wax polish.”

Other factors may be considered in selection, such as price criteria,performance criteria and appropriateness as detailed in U.S. PatentApplication No. entitled “Method And System For Providing TargetedGraphical Advertisements” filed Dec. 23, 2003, and in U.S. patentapplication entitled “System and Method for Rating Electronic Documents”filed Mar. 30, 2004 under Ser. No. 10/812,417.

In block 381, a rank and position may be determined for the one or moredocuments. In many embodiments, a rank is determined only when more thanone document is selected in block 371. For instance, the documents maybe provided in an ordered list (from the top down), and some documentsmay have specific other positions (e.g., a banner at the top of a webpage). The rank and position may be determined based on price andperformance information. For instance, a document with a high bid on akeyword may have a higher rank (and/or have a more prominent position)than a document with a lower bid on the same keyword when the documentsare provided in response to the keyword.

In block 391, the document may be passed to a user or content provider.In many embodiments, the document is passed to the entity that requestedthe document. For instance, it may be passed to the user who submittedthe search query. For instance, the document (or document link) maydisplayed as an image ad 1 in the search result page 3 shown in FIG. 4.

It will be appreciated to those skilled in the art that the actsdescribed may be performed by hardware, software, or a combinationthereof, with or without human intervention, as may be embodied in oneor more computing systems such as a server 2 system coupled to entitiessuch as providers, associating entities, databases, and end users.Further, it should be appreciated that not all of the blocks must beaccomplished. Also, it is not necessary that the action(s) of each blockbe performed in the order shown in FIG. 3. Any order of performance maybe considered, and some of the actions may overlap other actions.

Illustrative User Interface and Results

FIG. 4 shows an exemplary document 1 according to an embodiment of theinvention. FIG. 4 depicts an exemplary web page search result 3 from anInternet search engine. The web page 3 may be a document. Content on theweb page 1 may also be a document. For instance, advertisement 1 on thesearch result page 3 may also be a document. Other types of documentsmay be considered, such as advertisements, files, programs, and otherinformation.

The document may have various types of content. For instance, thedocument may have words, images, sounds, and other information, as wellas functions or programs, which may dynamically produce words, images,sounds, and other information. Each document may have different amountsof various types of content, such as sexual content, violent content,drug or alcohol-related content, financial content, adult-relatedcontent, child-related content, and other content.

FIG. 5 depicts an exemplary image advertisement document 1 according toan embodiment of the invention. The image ad 1 may comprise a banner ad,another ad that can be displayed on a web page, or another graphicaladvertisement that can be displayed via an electronic means. The imagead 1 shows specific images 1A, ad text 1B, one or more links 1C, and amechanism 1D for rating the document 1. The specific images 1A comprisea film projector and images of a DVD, VHS, and digital film container.The text 1B comprises an advertisement message, e.g., a description of aproduct or service, a suggestion to a potential customer, and/or otheradvertising text. The link 1C may comprise a link to another document,such as the advertiser's web page URL (or portion thereof). Forinstance, the link 1C may comprise an embedded hypertext link, and theembedded link may be associated with the link 1C displayed in the imageof the document 1. In some embodiments, selecting (e.g., clicking on)the displayed URL or other link while viewing the document 1 (e.g., in aweb browser) may direct the viewer's mechanism for viewing documents(e.g., web browser) to the content associated with the link (e.g., theadvertiser's web page).

The document 1 may explicitly display the link 1C. Alternately, the link1C may be embedded in the document (e.g., in the programming of thedocument) or a portion thereof such that the link 1C is not visible.Here, selecting (e.g., clicking on) the document 1, an image 1A, text1B, or another portion of the document may direct a user's documentviewing mechanism to the linked document(s). The document 1 itself,images 1A, and text 1C may also comprise one or more links 1C. Forinstance, an ad that advertises a plurality of products may comprise alink for each product, wherein selecting (e.g., clicking on) an image1A, icon 1A, or text 1B relating to a specific product may direct a webbrowser (or other document viewing mechanism) to a page at a merchant'ssite associated with the specific product (or to another document).

The mechanism 1D may comprise a link for providing concept associationinformation. For instance, selection of the mechanism 1D (e.g., clickingon the link 1D) may direct the document viewer to an email or web pagewhere the user may provide concept association information. Forinstance, the web page may comprise prompts for providing conceptassociation information or otherwise request concept associationinformation. Other mechanisms 1D for providing a communication linkbetween an associating entity and server 2 may be contemplated herein.

FIG. 6 depicts an exemplary document showing an ordered rankingaccording to an embodiment of the invention. Like FIG. 4, FIG. 6 showsan exemplary document 1 according to an embodiment of the invention,namely an exemplary web page 3 search result from an Internet searchengine. The web page 3 may be a document. Content on the web page 1 mayalso be a document. For instance, advertisement 1 on the search resultpage 3 may also be a document.

FIG. 6 shows two advertisements 1E, 1F in an ordered ranking on the page1. Advertisements 1E, 1F may be text or image ads or other documents.Here, advertisement 1E is listed above advertisement 1F. For instance,ad 1E may have a higher rank than ad 1F as determined by rank module 38.There may be any number of documents 1E, 1F, each displayed in an order(i.e., ranking) on the web page 3.

FIGS. 7-10 show exemplary interfaces according to an embodiment of theinvention. A server may provide the interface documents of FIGS. 7-10 toan ad purchaser on a webpage. An ad purchaser may comprise an individualor company representative who wants to purchase and/or create a text orimage ad, or it may comprise any entity that may select an ad or causean ad to be created.

The interfaces of FIGS. 7-10 may provide inputs to the ad purchaser sothat the ad purchaser may select various criteria related to the ad, asdescribed below. Each of FIGS. 7-10 may be used singly or in combinationwith one or more of the other FIGS. 7-10. For instance, one or more ofthe documents displayed in FIGS. 7-10 may link to one or more otherdocuments displayed in FIGS. 7-10. The documents shown in FIGS. 7-10 maycomprise links to other documents, help tools, and other documentelements commonly known in the art. The documents may be hosted by theserver 2 or the server's 2 agent, and the documents may be accessiblethrough the server's website or through other electronic means. Althoughthese figures are described in relation to a server 2 and ad purchaser,it should be appreciated that the documents described in FIGS. 7-10 maybe used for a variety of parties.

FIG. 7 shows a document 700 containing input fields for creating a textand/or image advertisement. The document 700 allows an ad purchaser toprovide inputs for creating a text ad or for creating an image ad. Forcreating a text ad, the input fields of document 700 enable an adpurchaser to input/select a headline 710 for the ad, ad descriptionline(s) 720, display URL 730, and destination URL 740. The headline 710may be displayed prominently in the ad, or it may be displayed at thetop of the ad or otherwise “headline” the ad. When the text ad isdisplayed, selecting the display URL 730 (which may be displayed in thead) may cause a user's browser to be directed to the destination URL740, which may be the same as (or different from) the display URL 730.For instance, the display URL 730 for an ad for a company's widget maybe “www.company.com” while the destination URL 740 for the ad may be“www.company.com/product/display/widget”. The document 700 may also showa sample text ad 4.

Document 700 may enable inputs/selections for image ads as well as textads (or other ads). Different inputs may be used when the ad purchasersupplies an image for the ad compared to situations where the adpurchaser does not supply an image. The document 700 may enable users toselect an image ad wizard document to guide the ad purchaser inselecting an image for the ad (see FIGS. 8-10). The image ad inputsavailable to the ad purchaser include a view input 750 for selectingresolution and/or other view characteristics of the ad, image input 760for inputting an image for the ad, and image name 770, in addition toinputs available for text ads such as display URL 730 and destinationURL 740. Document 700 may provide a browse input 780 for browsing adatabase (e.g., a hard drive of the ad purchaser's computer or anotherdatabase) from which to input an image, e.g., by uploading the image tothe server 2. Document 700 may also provide a save input 790 for savingthe text or image ad to a file, e.g., a file in a server database 50.

FIG. 8 shows a document 800 that allows an ad purchaser to input imagepreferences. A view input 750 allows the ad purchaser to select aresolution or layout for the ad, such as 468×60 banner ad, 120×600skyscraper ad, 728×80 leaderboard ad, and 300×250 inline ad. A keywordinput 810 may enable the ad purchaser to provide keywords that may beassociated with the ad by the server. Selecting a keyword suggestiontool input 820 may direct the ad purchaser to one or more keywordsuggestion tool documents 1100-1300, and/or it may cause the server 2 toprovide one or more suggested keywords. The server 2 may generate orselect suggested keywords based on the information received from the adpurchaser, such as the purchaser's ad heading, description, URL, etc.

After the ad is created, the ad may be selected for display by theserver 2 based on one or more keywords associated with the ad. Forinstance, if a requestor requests a document associated with a concept,the server 2 may provide the ad to the requestor if the ad is associatedwith one or more keywords related to the concept. The server may selectthe ad from among a plurality of ads based on the ad's (or the ad'skeywords') relevance to the concept and also based on one or more bidamounts for the one or more keywords. For instance, the requestor mayrequest search results related to a specific search query concept thatcomprises a plurality of search terms. The server 2 may receive therequest and provide search results along with one or more ads that areassociated with the highest bids on the terms in the search query.

The document 800 may also comprise image suggestion input 830, which maycause the server 2 to display a document 900 that comprises one or moresuggested images that may be used in the ad (see FIG. 9). The adpurchaser may then select one or more of the suggested images for use inthe ad. The document 800 may also display contextual help 840 that maycomprise information related to the ad creation process and/or relatedto the ad purchaser's selections and inputs.

FIG. 9 shows a document 900 that displays one or more images 902 (e.g.,suggested images) that may be used in the ad. The document 900 may bedisplayed in response to an ad purchaser's request to view or select asuggested image. The images 910 may be selected by the server 2 in anymanner described herein; e.g., the images may be selected based on userassociations that associate the images with one or more keywords orother concepts. The document 900 may comprise an image selector input920 that allows the ad purchaser to select one or more of the displayedimages 910 for inclusion in the image ad. The document 900 may alsocomprise one or more links 930 to additional images 910 (e.g.,additional pages of images 910).

The document 900 may also provide a text ad selector input 940 forenables the ad purchaser to cancel the image ad process and insteadprovide text ad inputs (e.g., in document 800).

FIG. 10 shows a document 1000 that enables an ad purchaser to customizean image ad 1. The document 1000 may comprise a color palette 1010 forselecting colors to be used in the ad, such as the background orforeground of the ad. The headline, description, and display URLcomponents of the ad may be customized separately. For creating a textad, the input fields of document 1000 enable an ad purchaser toinput/select a headline 710 for the ad, ad description line(s) 720,display URL 730, and destination URL 740. The display of each of thesefeatures may be customized by font and size, as well as other displayattributes. The document 1000 may also comprise a save input 1020 forsaving the ad (or other progress) to a database, such as a serverdatabase 50 or a database on the ad purchaser's computer system.

FIGS. 11-13 show an exemplary concept request template according to anembodiment of the invention. Specifically, FIGS. 11-13 show exemplarykeyword suggestion tool documents 1100-1300 that may enable the adpurchaser to select a keyword appropriate to the ad purchaser'spreferences, including price, language, concept relevance, number ofkeywords, etc.

FIG. 11 shows a keyword suggestion tool 1100 that may enable an adpurchaser to specify a type of keyword to associate with the ad. Theserver 2 may suggest keywords based on the purchaser's inputs indocument 1100. If an ad purchaser selects a “high traffic” option, theserver 2 may find synonyms to a keyword associated with an ad so thatthe ad can be associated with additional, related keywords. If an adpurchaser selects a “high clickthrough rate” option, the server 2 mayfind more specific variations of a keyword. If an ad purchaser selects a“match type comparison” option, the server 2 may show exemplary documentrequests that trigger the ad based on selected keywords (e.g., keywordsselected in the high traffic or high clickthrough rates options).

Keyword suggestion tool 1100 may enable ad purchasers to provide one ormore keywords or images to the server 2 during the keyword suggestionprocess. For instance, the user may elect to provide an image, at whichpoint the server 2 may prompt the ad purchaser for the image (seekeyword suggestion tool 1200 in FIG. 12). The server 2 may then processthe provided keywords and/or images to identify additional keywords andconcepts related to the provided images and/or keywords that may beassociated with the ad.

A language input 1110 may enable an ad purchaser to select one or morelanguages for the keywords. The server 2 may suggest keywords of theselected language(s). A keyword request input 1120 enables ad purchasersto request suggested keywords. In response to this input, the server 2may process the information input by the ad purchaser and identifypotential keywords. The server 2 may display the one or more suggestedkeywords to the ad purchaser (e.g., in another document), and the adpurchaser may select one or more of these keywords for inclusion in thead.

FIG. 12 shows a keyword suggestion tool 1200 that includes an imageprompt 1210 that prompts the ad purchaser for an image. It should beappreciated that tool 1200 may alternately (or in addition) prompt for akeyword at prompt 1210. Keyword suggestion tool 1200 may also havesimilar features to document 1100.

FIG. 13 shows a keyword-image suggestion tool 1300 for identifyingkeywords associated with a supplied image. The keyword-image suggestiontool 1300 may display an image 1A, such as an image provided by (orselected by) an ad purchaser (e.g., via document 700 or document 900).The keyword-image suggestion tool 1300 may enable ad purchasers to findkeywords related to (e.g., similar to or descriptive of) the suppliedimage. A format input 1310 may enable ad purchasers to select to viewthe image in a different format, e.g., a different size or resolution.The document 1300 may comprise instructions 1320 for selecting keywords.For instance, the instructions 1320 may instruct ad purchasers tohighlight (or otherwise select) one or more keywords provided in akeyword suggestion list 1330. The document 1300 may also display theselected keywords in a selected keyword list 1340. Ad purchaser inputsmay be saved at any time, e.g., via save input 1020.

Accordingly, the documents of FIGS. 7-13 may enable ad purchasers toinput ad information, and view suggested ads and keywords, and modifythose ads and keywords. Using these documents, ad purchasers may createone or more ads relating to one or more products and services, such asan entire ad campaign for a product.

It should be appreciated that while text and image advertisements areused as an example herein, the systems and methods described herein mayapply equally to other types of documents, such as web pages, emails,and other electronic documents.

It should be understood that the server, processors, and modulesdescribed herein may perform their functions (e.g., comparing a documentto another document or determining concept association information)automatically or via an automated system. As used herein, the term“automatically” refers to an action being performed by anymachine-executable process, e.g., a process that does not require humanintervention or input.

The embodiments of the present inventions are not to be limited in scopeby the specific embodiments described herein. For example, although manyof the embodiments disclosed herein have been described with referenceto image ads, the principles herein are equally applicable to otherdocuments, such as websites. Indeed, various modifications of theembodiments of the present inventions, in addition to those describedherein, will be apparent to those of ordinary skill in the art from theforegoing description and accompanying drawings. Thus, suchmodifications are intended to fall within the scope of the followingappended claims. Further, although the embodiments of the presentinventions have been described herein in the context of a particularimplementation in a particular environment for a particular purpose,those of ordinary skill in the art will recognize that its usefulness isnot limited thereto and that the embodiments of the present inventionscan be beneficially implemented in any number of environments for anynumber of purposes. Accordingly, the claims set forth below should beconstrued in view of the full breath and spirit of the embodiments ofthe present inventions as disclosed herein.

1. A computer-implemented method for generating an electronicadvertisement, the method comprising: receiving, at a server, a requestfrom an advertiser to generate an electronic advertisement associatedwith a concept; suggesting, by the server, presentation content to theadvertiser for inclusion in the electronic advertisement, wherein thesuggested presentation content is based, at least in part, on theconcept; receiving, at the server and from the advertiser, a selectionof the suggested presentation content; receiving, at the server, apresentation layout indication from the advertiser; automaticallygenerating, at the server, the electronic advertisement for theadvertiser using the selected suggested presentation content and thepresentation layout indication, wherein the advertisement comprises atleast part of the selected suggested presentation content that wassuggested by the server; associating one or more keywords with theelectronic advertisement; and storing the electronic advertisement andthe associated one or more keywords such that it may be retrieved inresponse to a user query received in the future upon comparison with theassociated one or more keywords.
 2. The method of claim 1, wherein theelectronic advertisement comprises an image ad.
 3. The method of claim2, wherein the suggested presentation content comprises a plurality ofimages.
 4. The method of claim 1, wherein the electronic advertisementcomprises a text ad.
 5. The method of claim 4, wherein the suggestedpresentation content comprises a plurality of text items, and whereinthe selection comprises a selected text item, and wherein the text adcomprises the selected text item.
 6. The method of claim 1, wherein theelectronic advertisement comprises at least one of an image ad or a textad, and wherein the suggested presentation content comprises at leastone of a plurality of images, or a plurality of text suggestions forinclusion in the electronic advertisement.
 7. The method of claim 6,wherein the electronic advertisement comprises a banner ad.
 8. Themethod of claim 1, wherein the electronic advertisement comprises atleast one of an email or a web page.
 9. The method of claim 1, whereinthe electronic advertisement comprises at least one of an image,animation, pop-up ability, sound, voice, or music.
 10. The method ofclaim 1, wherein the concept comprises one or more images or text items,and wherein the act of generating the document comprises: incorporatingthe at least one of the one or more images or text items into theelectronic advertisement.
 11. The method of claim 1, further comprising:requesting at least one of an image or a text item as part of therequest; receiving at least one of an image or a text item in responseto the act of requesting at least one of an image or a text item as thesuggested presentation content, wherein the generated document comprisesthe received at least one of an image or a text item.
 12. The method ofclaim 1, further comprising: automatically generating a plurality ofsuggested advertisements based at least in part on the request, theconcept, and the selected content; receiving a selection of one of theplurality of suggested advertisements; storing the selectedadvertisement in a database of advertisements for subsequent provisionto third parties.
 13. The method of claim 1, further comprising:generating an ad campaign comprising a plurality of ads based on therequest.
 14. The method of claim 1, wherein the suggested presentationcontent comprises at least one image selected from a database ofapproved, public images.
 15. The method of claim 1, wherein the conceptcomprises at least one of an image, animation, pop-up ability, sound,voice, or music.
 16. The method of claim 1, further comprising:associating the electronic advertisement with the selected content. 17.The method of claim 1, wherein the electronic advertisement is linked tothe concept and is operable to be served in response to a request forsearch results from a search engine, and wherein the concept comprisesat least one keyword associated with the search results.
 18. The methodof claim 1, wherein the electronic advertisement comprises the selectedcontent.
 19. The method of claim 1, wherein the request is a request foran image ad associated with at least one of a keyword and an image. 20.The method of claim 1, further comprising: receiving one or moreformatting preferences, wherein the electronic advertisement isgenerated based on the one or more formatting preferences.
 21. Themethod of claim 20, wherein the one or more formatting preferencescomprise at least one of an image size preference, image resolutionpreference, text size preference, document size preference, documentshape preference, color preference, or font preference.
 22. The methodof claim 21, further comprising: identifying an image to include in theelectronic advertisement; and processing the image based on the one ormore formatting preferences.
 23. The method of claim 1, furthercomprising: receiving at least one of a display URL and a destinationURL; and associating the at least one of a display URL and a destinationURL with the document.
 24. The method of claim 1, further comprising:receiving a clickthrough rate preference, wherein the suggestedpresentation content is selected based on the clickthrough ratepreference.
 25. The method of claim 1, further comprising: receiving aprice parameter preference, wherein the suggested presentation contentis selected based on the price parameter preference.
 26. The method ofclaim 25, wherein the price parameter preference may comprise a selectedbid amount.
 27. The method of claim 1, further comprising: receiving atleast one of a language and country preference, wherein the suggestedpresentation content is selected based on the at least one of a languageand country preference.
 28. The method of claim 1, further comprising:suggesting a plurality of keywords to associate with the electronicadvertisement; receiving at least one selected suggested keyword; andassociating the electronic advertisement with the at least one selectedsuggested keyword.
 29. The method of claim 1, further comprising: usingan image processor to identify subject matter in an image, wherein thesuggested presentation content comprises the image, and wherein the actof suggesting is based on an association between the identified subjectmatter and the concept.
 30. The method of claim 1, wherein the conceptcomprises a graphic, the method further comprising: automaticallyprocessing the graphic to identify at least one of a word and an imagein the graphic, wherein the suggested presentation content is based onthe identified at least one of a word and an image.
 31. The method ofclaim 30, wherein the advertisement comprises the identified at leastone of a word and an image.
 32. The method of claim 1, wherein theconcept comprises an image, further comprising: reading optical datafrom the image to identify text, wherein the suggested presentationcontent is selected based on the identified text.
 33. The method ofclaim 32, wherein the text is identified using optical characterrecognition.
 34. The method of claim 1, wherein the concept comprises animage, further comprising: reading optical data from the image by animage processor to identify at least one image, wherein the suggestedpresentation content is selected based on the identified at least oneimage.
 35. The method of claim 1, wherein the concept comprises animage, further comprising: reading optical data from the image by animage processor to determine whether the image is associated with any ofa plurality of graphical documents stored in a database.
 36. The methodof claim 1, wherein the concept comprises an image, further comprising:reading optical data from the document to determine whether the image issubstantially identical to any of a plurality of images stored in adatabase.
 37. The method of claim 1, wherein the suggested presentationcontent is selected based on one or more concept associations, whereineach of the one or more concept associations comprise a selection of adocument from among a plurality of documents associated with a concept.38. The method of claim 37, wherein the plurality of documentsassociated with a concept comprises a plurality of search resultsassociated with a search query.
 39. The method of claim 37 wherein thesuggested presentation content is selected from a database comprising aplurality of documents each associated with one or more identifiedideas, and wherein the suggested presentation content is selected basedon a relevance between the identified ideas and the concept.
 40. Themethod of claim 1, further comprising: receiving one or more userconcept associations, wherein each user concept association associatesan advertisement with a concept; and storing the one or more conceptassociations, wherein the suggested presentation content is based on theone or more concept associations.
 41. The method of claim 40, whereinthe one or more concept associations comprise a selection of a documentfrom among a plurality of documents associated with a concept.
 42. Themethod of claim 41, wherein the concept associated with the plurality ofdocuments comprises a search query, and wherein plurality of documentsare provided to a user in response to the search query.
 43. The methodof claim 1, further comprising: receiving a request for a documentassociated with an idea; and responsive to the request, delivering theelectronic advertisement if an association between the idea and theselected content is determined.
 44. The method of claim 43, furthercomprising: selecting the electronic advertisement for delivery based ona distance in semantic space between the idea and the selected content.45. The method of claim 43, wherein the electronic advertisement isdelivered to at least one of an end-user and a provider.
 46. The methodof claim 43, wherein the electronic advertisement comprises a targetedadvertisement, and wherein the delivering action comprises providing thetargeted advertisement on at least one of a content page or a searchresult page.
 47. The method of claim 43, wherein the electronicadvertisement is associated with an entity, and the act of deliveringthe electronic advertisement comprises: positioning the electronicadvertisement for display based on a ranking among advertisements forthe concept, the ranking being based at least in part on a priceparameter offered by the entity.
 48. The method of claim 47, wherein theentity is offered an incentive to provide at least one electronicadvertisement.
 49. The method of claim 47, wherein a premium isassociated with the electronic advertisement.
 50. The method of claim47, wherein the ranking is further based at least on a performanceparameter associated with the electronic advertisement.
 51. The methodof claim 50, wherein the performance parameter is automatically adjustedbased on one or more of predetermined time passed and predeterminednumber of clicks.
 52. The method of claim 50, wherein the ranking iscalculated by multiplying the price parameter and the performanceparameter.
 53. The method of claim 50, wherein one or more of the priceparameter and the performance parameter is adjusted based on a type ofelectronic advertisement.
 54. The method of claim 1, further comprising:receiving a conversion rate preference, wherein the suggestedpresentation content is selected based on the conversion ratepreference.
 55. The method of claim 1, wherein the method is implementedon a server.
 56. The method of claim 1, further comprising requesting anindication of presentation layout from the advertiser.
 57. Acomputer-implemented method for generating a graphical advertisement,the method comprising: receiving from a sender and at a server, an imageand a request to generate a graphical advertisement associated with theimage; suggesting to the sender and by the server graphics and text forinclusion in the graphical advertisement based on the image; suggestingto the sender and by the server a keyword to associate with thegraphical advertisement; receiving from the sender and at the server aselected keyword; associating the graphical advertisement with theselected keyword; receiving from the sender and at the server aselection of the suggested graphics and text; and automatically, at theserver, generating the graphical advertisement using the selectedsuggested graphics and text.
 58. The method of claim 57, wherein: thereceived image and request are received from an advertiser; thesuggested graphics, text, and keyword are suggested to the advertiser;and the selected suggested graphics, text, and keyword are received fromthe advertiser.
 59. A computer-implemented method for generating agraphical advertisement, the method comprising: receiving from anadvertiser text and a request to generate a graphical advertisementassociated with the text; suggesting, by a server, graphics and wordsfor inclusion in the graphical advertisement based on the text includingproviding the suggestions to the advertiser; receiving from theadvertiser and at the server a selection of at least one of thesuggested graphics and words; receiving, at the server, a presentationlayout indication; suggesting to the advertiser and by the server one ormore keywords to associate with the graphical advertisement; receivingfrom the advertiser and at the server a selected keyword; associatingthe graphical advertisement with the selected keyword; and automaticallygenerating by the server the graphical advertisement using the selectedgraphics and words and the presentation layout indication.
 60. Themethod of claim 59, wherein: the received text is received from anadvertiser; the suggested graphics, words, and keyword are suggested tothe advertiser; and the selected suggested graphics, words, and keywordare received from the advertiser.
 61. A system for generating adocument, the system comprising: an advertiser interface operable toreceive a request from an advertiser to create an electronicadvertisement associated with a concept, the advertiser interface beingfurther operable to provide suggested presentation content to theadvertiser for inclusion in the electronic advertisement and receivefrom the advertiser a selection of at least a portion of the suggestedpresentation content and a presentation layout indication; a databasefor storing content; a processor for automatically identifying andsuggesting presentation content and one or more keywords for theelectronic advertisement based, at least in part, on the concept andproviding the suggested presentation content and one or more keywords tothe advertiser through the advertiser interface; a document generatorfor automatically generating the electronic advertisement using theselected suggested presentation content and the presentation layoutindication, wherein the electronic advertisement comprises at least partof the selected suggested presentation content; and a database forstoring the electronic advertisement such that it may be retrieved inresponse to a user query received in the future and associated with theconcept.
 62. An article of manufacture comprising a computer-readablemedium encoded with computer program code executable by one or moreprocessors to generate a document, the program code effective to performthe following: receive a request from an advertiser to generate anelectronic advertisement associated with a concept; suggest, by a serverand to the advertiser, presentation content for inclusion in theelectronic advertisement and one or more keywords for association withthe electronic advertisement, the suggested presentation content beingbased, at least in part, on the concept; receive from the advertiser aselection of at least a portion of the suggested presentation content;receive a presentation layout indication from the advertiser; andautomatically generate, by the server, the electronic advertisement forthe advertiser using the selected suggested presentation content and thepresentation layout indication, wherein the electronic advertisementcomprises at least part of the selected suggested presentation content.